At a glance
Share of Bring consignments that hit a non-delivery exception event in the period: held at terminal, address invalid, recipient absent, customs delay, weather hold, or other interruption that breaks the normal “booked → in transit → delivered” flow. Exceptions do not always become late deliveries (most resolve within 24 hours), but a rising exception rate is the leading indicator that next week’s On-Time Delivery Rate and Late Shipments will move down. Treat this as the early-warning dial on Bring carrier health.
Calculation
Calculated automatically from your Bring data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
The Drammen-based outdoor-apparel merchant, 15,300 trailing-30-day Bring consignments. Reading taken at 09:00 CET on 11 Mar 26 for the trailing 30 days (10 Feb 26 to 10 Mar 26).
The dial reads 2.79 percent; warn at
>3% is not tripped, but the trend matters more than the level. Five things to notice:
- Held-at-terminal is the largest bucket and the most resolvable. 142 consignments held at terminal usually means a sortation backlog at one or two specific facilities. If the bulk is at the Oslo Alfaset terminal, a quick peak-shift conversation with the Bring account team typically resolves it; if it is at a partner-handover terminal in Sweden or Denmark the resolution is slower.
- Recipient-absent is structural, not an issue. 98 absent-recipient exceptions on Home Delivery is normal for residential Norway; recipients work, parcels go to pickup point, recipients collect within 48 hours. The healthy reading is around 0.5 to 1 percent of Home Delivery volume; this merchant’s 1.3 percent is within range.
- Weather delay is seasonal noise to annotate, not act on. 71 weather-delay exceptions in March is the tail end of winter; in July this category will read close to zero. Do not re-baseline the alert threshold for weather; instead note the seasonal pattern in the board commentary.
- Address-unknown is the merchant’s problem, not Bring’s. 44 unknown-address exceptions usually trace back to the checkout flow: missing apartment numbers, unit numbers, postcode mismatches. Pair with
shopify.checkout_address_validationor equivalent, and consider a checkout address-validator if the count exceeds 0.4 percent. Each address-unknown exception costs roughly 25 to 45 minutes of CS time to resolve. - Lost-in-transit is the small number that hurts most. 3 lost-in-transit consignments at an average order value of 850 NOK each = 2,550 NOK of refund-or-reship liability, plus 3 angry customers and 3 negative reviews. Treat lost-in-transit as a separate dial; the Open Claims card breaks these out and tracks claim-recovery time.
Sibling cards merchants should reference together
Exception Rate is a leading indicator. Pair it with these to read the signal:Reconciling against the vendor’s own dashboard
Where to look in Bring’s own portal: Mybring → Statistics → Tracking Events, then filter the event-code dropdown to the exception classes (held-at-terminal, address-unknown, recipient-absent, customs-inspection, weather-delay, damaged, lost). Mybring presents the data as an event count rather than as a per-consignment rate; the card normalises to per-consignment to avoid double-counting. Why our number may legitimately differ from Mybring:
Cross-connector reconciliation:
Known limitations / merchant FAQs
Should I exclude weather delays from the alert threshold during winter? Reasonable choice. Norwegian winter on northern routes (postcode 90xx and above) generates a structural 0.5 to 1.5 percent weather-delay exception rate from November through March. The card reports the gross rate; configure the alert at the integration layer to either (1) excludeweather_delay from the alert formula during winter months, or (2) raise the threshold from 3 percent to 4 percent for that window. Do not delete weather exceptions from the underlying data; they are real and you may want to comment on the customer-felt experience separately.
My exception rate is 4 percent and OTD is still 96 percent. Is this fine?
Probably yes. The relationship is leading-indicator, not equivalence. If exceptions are running 4 percent but resolving inside the promise window (sortation backlog cleared in 6 hours, recipient-absent collected next morning) the OTD dial is unaffected. Watch the trend: if exception rate keeps climbing while OTD stays flat, you are riding a recovery margin that will eventually exhaust. If OTD starts falling 24 to 72 hours after the exception spike, the recovery margin has run out.
A single warehouse error caused 200 address-unknown exceptions in one day. Is the dial broken?
The dial is reading reality. A label-data export bug or a checkout typo can produce a one-day spike. The card does not auto-smooth; configure your alert to trigger on a 7-day rolling rather than daily reading if one-day spikes are too noisy for your operations cadence. The underlying data should still be fixable: identify the affected consignments via the drill-down, contact Bring to update addresses (the parcels are usually still in network and re-deliverable), and patch the upstream cause.
Why does my Cross-Border exception rate read so much higher than my Norwegian-domestic rate?
Three structural reasons. (1) Customs inspections. EU + Norway is not a frictionless border for parcels above 350 NOK; customs inspections for non-EU origin (or non-Norway-EFTA exemptions) add 1 to 3 percentage points of customs_inspection exceptions. (2) Partner-carrier hand-overs. Each hand-over (Bring → PostNord → DHL last-mile) is an opportunity for a hand-over scan to fail or get logged as an exception. (3) Address-format mismatches. Norwegian, Swedish, Danish, and Finnish postcode formats differ; a checkout that does not validate per-country generates 0.5 to 2 percent extra address-unknown exceptions on cross-border. The fix for (1) is to ensure correct customs-data on the booking; the fix for (2) is structural and outside the merchant’s control; the fix for (3) is a per-country-aware checkout validator.
Held-at-terminal keeps showing up. Should I worry?
Held-at-terminal is the most common exception code and usually the least concerning; it just means the parcel paused at a sortation facility. Concerning patterns: (1) consistently held at the same terminal more than 24 hours, suggesting a local capacity problem, (2) held-at-terminal on the same lane every Monday, suggesting a recurring weekend backlog, (3) held-at-terminal followed by lost-in-transit, suggesting the parcel actually went missing during the hold. Use the drill-down to identify the terminal pattern; raise it with your Bring account team if it is a single-facility issue.
Which exception codes should I treat as actionable vs ignorable?
Actionable (chase same-day): damaged_in_transit, lost_in_transit, incorrect_address (when paired with a high-value consignment), recipient_refused. Actionable (chase within 24 hours): address_unknown, customs_inspection exceeding 48 hours. Monitor only: held_at_terminal, recipient_absent, delivery_attempted, weather_delay. The alert threshold of 3 percent is calibrated to the actionable + monitor mix; if you split the alert into “actionable-only”, set it lower (around 1 percent).
My CS team wants a webhook for new exceptions, not a periodic dashboard read. Is that supported?
Yes. Configure the Bring webhook integration to push exception events to your CS tool (Gorgias, Zendesk, etc.) with eventCode IN exception_set as the filter. Pair with Klaviyo Transactional Email to send a proactive customer email on the same trigger. The card itself reads from the same event stream; webhook + dashboard reads are consistent.
The dial dropped from 2.8 percent to 0.4 percent overnight. Did the network suddenly improve?
Probably not. Most overnight dial drops on this card are data-feed issues, not network improvements. Three things to check: (1) is the Bring tracking-API integration still authenticated (see Days to Token Expiry), (2) is the booking-API integration still posting (a missing booking flow means newer parcels are not in the denominator), (3) is there a consignment-number mismatch between booking and tracking (a recent service-code rename can break the join). If all three are healthy and the drop is real, double-check by comparing against Late Shipments; the two should move in directionally consistent ways.
Is the 3 percent threshold suitable for a B2B-heavy merchant?
Mostly yes. Bring Business Parcel Bulk B2B has a structurally lower exception rate than residential (roughly 0.5 to 1 percent vs 1 to 2 percent for residential) because B2B receivers are at fixed addresses with goods-in operations. A B2B-heavy merchant might tighten the alert to 2 percent. A B2C-heavy merchant on Cross-Border is comfortably above 3 percent on a normal week and may need to loosen to 4 percent or split per-route.